In this paper, we aim to introduce a new perspective when comparing highly parallelized algorithms on GPU: the energy consumption of the GPU. We give an analysis of the performance of linear algebra operations, including addition of vectors, element-wise product, dot product and sparse matrix-vector product, in order to validate our experimental protocol. We also analyze their uses within conjugate gradient method for solving the gravity equations on Graphics Processing Unit (GPU). Cusp library is considered and compared to our own implementation with a set of real matrices arrising from the Chicxulub crater and obtained by the finite element discretization of the gravity equations. The experiments demonstrate the performance and robustness of our implementation in terms of energy efficiency.
翻译:在本文中,我们的目标是在比较GPU高度平行的算法:GPU的能量消耗时引入新的视角。我们分析了线性代数操作的性能,包括增加矢量、元素产品、点产品和稀有的矩阵矢量产品,以验证我们的实验协议。我们还分析了在解决图形处理器重力方程式(GPU)重力方程式(GPU)的同比梯度法内这些算法的用途。Cusp图书馆被考虑,并比较了我们自己的执行情况,用一套由Chicxulub弹坑产生、通过重力方程的有限分解要素获得的真基质矩阵。这些实验显示了我们在能源效率方面执行的性能和稳健性。